Abstract—In this study, we used the digital television signal

broadcasted by geostationary satellite for passive bistatic synthetic

aperture radar (SAR) imaging and interferometry applications. A

prototype system was designed and fabricated with commercial-

off-the-shelf (COTS) components. Specifically, three low noise

block downconverters (LNBs) were synchronized for a long-time

coherent measurement. Moreover, multiple TV channels were

combined to achieve a wider frequency bandwidth to improve the

range resolution. The potential applications of this ground-based

radar system are SAR imaging, displacement estimation, and

digital elevation model (DEM) generation. Hardware design and

data processing algorithms are described. Experimental results

are presented to validate the performance of the designed system

and the proposed methods.

Index Terms—Passive bistatic radar (PBR), Satellite digital TV

signal, Synthetic aperture radar (SAR), SAR interferometry.

I. INTRODUCTION

Recently, passive bistatic radar that uses existing broadcasting

signals, communication signals, and navigation signals has

drawn a lot of interests [1-2]. Compared to other illuminators of

opportunity, such as WiFi and terrestrial TV signal, PBR using

satellite digital TV signal has several advantages, including: 1)

one TV channel can provide a frequency bandwidth larger than

30 MHz; if multiple TV channels are combined, a bandwidth

larger than 150 MHz and thus a sub-meter range resolution can

be obtained; 2) since its working frequency is at Ku band, a

high-resolution change detection capability via interferometry

technique can be achieved, like that in ground-based SAR [3-

4]; 3) a larger illumination area and a clearer reference signal

increase the usability and performance of the PBR system. For

example, digital TV broadcasting with Broadcasting Satellite

(BS) on the geostationary orbit of 110 degrees East longitude

(BS 110°E) can provide services for the whole area of Japan.

However, there are also some difficulties when using the

satellite TV signal for PBR applications, including: 1) the

power density of the satellite TV signal on the Earth surface is

normally much lower than some other signals used for PBR

applications, such as FM and DAB, resulting in a lower signal

to noise ratio (SNR) and a shorter detection range; 2) if some

commercial-off-the-shelf (COTS) components are used to

reduce the system cost, some modifications must be conducted

to synchronize both frequency and phase between the reference

channel and the surveillance channels for long-time coherent

measurement; 3) the waveform of the digital TV signal is not

designed for radar applications, its signal structure, including

spectrum properties, pilot signals, and guard intervals, will

introduce undesired artifacts in the range direction when the

classical cross-correlation processing method is used; 4) when

multiple frequency bands were combined to increase the range

resolution, frequency gaps among different TV channels cause

high-level artifacts in the range direction [5].

To solve these problems, we proposed a hardware design

method and several processing algorithms in this paper. Firstly,

we describe an LNB synchronization method to increase the

integration time for SNR improvement. Secondly, we use the

inverse filter technique to reduce the influence of the TV signal

structure. Thirdly, we apply the super spatially variant

apodization (Super-SVA) method to fill the frequency gaps

among multiple TV channels to suppress the artifacts. Finally,

based on a PBR prototype system using COTS components,

SAR imaging and displacement estimation experiments are

carried out to validate the proposed methods.

II. DESIGNED SYSTEM OVERVIEW

A. Adopted ISDB-S signal

Fig. 1. The spectrum of the satellite TV signal in Japan.

The spectrum of the used satellite TV signal is shown in Fig.

1, where the local oscillator frequency of LNB is about 10.601

GHz. BS and communication satellite (CS) signals are

broadcast by different satellites that are on the geostationary

orbit of 110 degrees East longitude (110°E). Each TV channel

has a frequency bandwidth of 34.5 MHz. If twelve channels of

BS or CS are combined, a 475.5 MHz frequency bandwidth can

be achieved, resulting in a maximal bistatic range resolution of

0.32 m. We note that, in this study, only CS signal is used for

simplicity. BS signal transmitted via both left-hand and right-

PASSIVE BISTATIC SAR IMAGING AND INTERFEROMETRY BY SATELLITE

DIGITAL TV SIGNAL

1Weike Feng, 2Jean-Michel Friedt, 3Giovanni Nico, 2Gilles Martin, 4Motoyuki Sato

1Graduate School of Environmental Studies, Tohoku University, Sendai, Japan

2FEMTO-ST, Time & Frequency department, Besancon, France 3Consiglio Nazionale delle Ricerche, Istituto per le Applicazioni del Calcolo, Bari, Italy

4Center for Northeast Asian Studies, Tohoku University, Sendai, Japan

hand circular polarizations will be used for multi-polarization

applications in the near future.

B. Designed radar system

The designed radar system is shown in Fig. 2. It has three

parallel receiving channels, one reference channel and two

surveillance channels. For reference channel, a 45-cm parabolic

antenna is used, while only the feed-horns of parabolic antennas

are used for the surveillance channels to achieve a wider beam-

width. Three LNBs with a local frequency of 10.601 GHz are

synchronized by an oscillator controller. To further amplify the

received signal, three COTS BS/CS boosters were used, whose

working frequency is from 10 to 2600 MHz and gain is from 26

to 34 dB adjustable. Surveillance antennas are mounted on a

positioner to generate a synthetic aperture with a fixed step in

the horizontal direction. The signal flow will be sampled by a

digital storage oscilloscope with a sampling frequency of 10

GHz. Finally, the acquired raw data are transferred to a local

PC for off-line signal processing, consisting in frequency gaps

filling, SAR imaging, and interferometric processing.

Fig. 2. The designed PBR system using satellite TV signal.

C. LNB synchronization

Since COTS LNBs have different local oscillators, their

phase differences will reduce the coherence of the three

receiving channels. When the data are sampled in a short time,

the phase difference is approximately caused by their local

frequencies only. Thus, a simple phase difference estimation

method can be used [5], consisting in: 1) Divide the signal into

U short-length (T) subsets, within which the phase difference is

assumed to be constant, i.e., f1t and f2t, where t=[0, T, ... , (U-

1)T], f1 and f2 are the frequency differences between the

surveillance LNBs and the reference LNB; 2) Do cross-

correlation between the co-located reference and surveillance

antennas to obtain the phase of peaks in each subset, which

gives e−j2πf1t and e−j2πf2t; 3) Finally, do Fourier transform of the

peak phases, providing us with f1 and f2.

However, since SAR imaging and interferometric processes

are desired and a longer integration time can increase the SNR

and increase the detection distance, coarse phase correction is

not enough. Thus, an advanced LNB synchronization approach

is further proposed, whose setup is shown in Fig. 3. Based on

the unpublished NXP application note "X-tal driver for using

multiple TFF10xx to the same X-tal as reference" describing

the mechanism for locking multiple TFF10xx PLLs on the same

reference as desired, a dedicated Pierce oscillator was built

around a 25 MHz resonator and a 74HC04 inverter. The output

of the Pierce oscillator feeds another 74HC04 used to generate

three sets of in-phase and phase-opposition (180-degree phase

shift) signals feeding the PLL inputs. Care must be taken on the

one hand to tune the output voltage amplitude to acceptable

levels (500 mVpp) using a voltage divider bridge, and on the

other hand to include a DC-blocking capacitor (5.6 nF) between

the oscillator output and the PLL to avoid DC-current leakage

from the PLL, which would prevent PLL locking. Under the

proper conditions, frequency/phase coherence was observed to

be stable over tens of minutes, as needed for SAR measurement.

Fig. 3. LNB synchronization setup.

III. INVERSE FILTER AND FREQUENCY GAP FILLING

A. Cross-correlation and inverse filter

Normally, a cross-correlation method is used to estimate the

delay of the target, given by

0( ) ( ) ( )

intTa

a sur refs t s t dt (1)

which can be implemented by Fast Fourier Transform, giving

( ) [ ( ) ( ) ]H H a

a sur ref

s f s f s f (2)

where sref(t) is reference signal, ssur(t) is surveillance signal, a =

1 or 2 denotes the first or the second surveillance channel, (·)∗

denotes the complex conjugate, χ(τ) is the range-compression

result, τ is the expected time delay of the target, Tint is the

integration time, Φ is the Fourier transform matrix, denotes

element-wise multiplication, sref(f) and ssur(f) are the frequency

domain signals of the reference and surveillance channels.

However, since the waveform of satellite TV signal is not

designed for radar applications, the cross-correlation processing

will introduce high-level artifacts in the estimation. A simple

but effective method to solve this problem is to use an inverse

filter to avoid the influence of the signal structure of the TV

signal, which can be expressed as 2( ) [ ( ) ( ) / | ( ) | ]H H a

a a sur ref ref

's f s f s f s f (3)

B. Frequency gap filling

To improve the range resolution, multiple TV channels can

be combined to obtain a wider bandwidth. However, different

TV channels are separated by frequency gaps to guarantee a

high-quality signal transmission, introducing artifacts into the

range compression result. Several spectral gaps filling methods

can be used, such as auto-regressive (AR) based method, Super-

SVA based method, and sparsity and low-rank property based

methods [5]. In this paper, Super-SVA method is used for its

simplicity and effectiveness. Based on the SVA algorithm, the

range compression result of the n-th (n = 1, 2,...,12) TV channel

is given by

Osc

illo

sco

pe

Ant. Ref

Ant. Surv-1

Co

ntr

oll

er a

nd

off

-

lin

e si

gn

al p

roce

sso

r

Position

controller

Ant. Surv-2

Pos

itio

ner

LNB oscillator controller

LO1LNB1

LO2LNB2

LO3LNB3 Booster

Booster

Booster

Target

, ,[ ( ) ( )]SVA H

a n n a n 's f W f (4)

where ( )W f is a nonlinear “cosine on pedestal” weighting

function that can be expressed as

( ) 1 2 cos(2 / ), 0 0.5W m m M (5)

Then, the frequency gaps can be filled by Super-SVA via the

following steps:

1) Perform Fourier transform of ,

SVA

a n to get , ( )SVA

a n f ;

2) Apply an inverse weighting vector ( )invW f to obtain

, ,( ) ( ) / ( )S SVA SVA

a n a n invW s f f f ;

3) Replace the center portion of the extrapolated signal

, ( )S SVA

a n

s f with the original signal

, ( )a n

's f .

According to this procedure, the gapped signal can be

reconstructed for each TV channel. Since two adjacent channels

have the same gapped frequencies, a simple average process

can be used to obtain the final estimation. Finally, the range

compression can be obtained by ( )S SVA H S SVA

a a

s f .

IV. SAR IMAGING AND INTERFEROMETRY

Fig. 4. SAR imaging geometry.

The imaging geometry of the designed radar system is shown

in Fig. 4, where the reference antenna is located at (0, 0) and the

surveillance antenna is scanned along a rail from ( / 2, )a

surL y

to ( / 2, )a

surL y with L as the synthetic aperture length. The

elevation angle of the satellite is 35.3sat in Sendai (Japan)

area. For the o-th (o=1, 2,..., O) surveillance antenna position,

the range compression can be conducted by applying Fourier

transform to the gap filled signal, giving , , ( )S SVA H S SVA

a o a o

s f .

Then, the SAR image of the target can be obtained by applying

the back projection (BP) algorithm, giving

, 1 21[ (( ) )],

O S SVA a

a ooa x R R oy

(6)

where ( , )a x y is the estimated amplitude of the point at (x, y),

1R is the path difference between the TV satellite to the target

and to the reference antenna, 2 2

2 ( )= ( ) ( )a a

o surR o x x y y is

the distance from the target to the o-th antenna position of the

a-th surveillance antenna, and , 1 2[ ( )]S SVA a

a o R R o can be

calculated by the linear interpolation process. Since the satellite

is far from the experiment position, i.e., |yT| is much bigger than

x and y, 1R can be approximately calculated by

2 2

1 ( )T TR x y y y y (7)

The designed passive radar system can acquire a time series

of 2D SAR images of the scene with a temporal baseline of few

minutes as the used geostationary satellite is continuously

illuminating the area of interest. This allows many interesting

interferometric SAR applications. For each pair of SAR images,

an interferometric phase image can be generated by

- ( , ) ( ,a ) (r )},g{ mater slD I aven x y x y x y

(8)

As an application, the displacement of a target can be

estimated by the relationship - ( , ) / 4D InD x y , where λ is

the wavelength, which is 24 mm for the CS signal. Besides, we

note that, since two surveillance antennas can be used, the

developed system can also generate a high resolution Digital

Elevation Model (DEM) of the imaging scene by properly

setting a spatial baseline between the two surveillance antennas.

DEM generation experiments are on-going and will be further

researched.

V. EXPERIMENT RESULTS

In this section, some experimental results will be shown to

validate the designed radar system and the proposed processing

methodologies. At the beginning, a time delay estimation

experiment using the satellite TV signal was conducted, as

shown in Fig. 5, where two parabolic antennas with

synchronized LNBs were faced toward the CS 110°E satellite.

Twelve TV channels were combined and inverse filter is used

for range compression. The estimation results are shown in Fig.

6, where two different integration times are assessed. As we can

see, by increasing the integration time from 1 μs to 100 μs, the

SNR can be increased about 10 dB, which proves that the LNBs

are well synchronized. Otherwise, the SNR will not be

increased but decreased because the two receiving channels are

not coherent [5].

Fig. 5. Time delay estimation experiment setup.

Fig. 6. Delay estimation results with different integration time.

However, as indicated by the black circle in Fig. 6, high-level

periodical artifacts will be generated by the frequency gaps. By

applying Super-SVA based frequency gap filling method, these

artifacts can be well suppressed, as shown in Fig. 7, where the

0 0( , )x y

0 0( , )

,( )a

o surx y

y

x

1R

2R

sat

0x

0y

0,( )Ty

integration time is 100 μs. Furthermore, in order to check the

coherence of two channels, 250 measurements were conducted

with a period of 5 minutes, and the peak phase of the result was

extracted, as shown in Fig. 8. It is observed that, the peak phase

difference has a mean value of -0.16 degree and a standard

deviation of 2.50 degree for 250 measurements.

Fig. 7. Delay estimation result obtained by filling frequency gaps.

Fig. 8. Phase stability evaluation for 250 measurements.

Based on the aforementioned methodologies, passive bistatic

SAR imaging experiments were carried out, as shown in Fig. 9,

where the surveillance antenna is sled along a rail to detect a

metallic plate. The moving step was 5 mm and the total sledding

length was 1.2 m. The range compression results for each

surveillance antenna position and the SAR image obtained by

the BP algorithm are shown in Fig. 10. As we can see, the

metallic plate can be well detected and focused.

Fig. 9. SAR imaging of a stationary metalli plate.

Fig. 10. Top: Range compression results. Bottom: SAR image.

At last, the displacement of the metallic plate, which was

moved on a rail from 1 mm to 15 mm with a 1-mm step, was

estimated. The acquisition time of each SAR image was about

45 seconds. The estimation results are shown in Fig. 11. It can

be seen that the displacement of the metallic plate can be

accurately estimated. The root mean square error (RMSE) of

the estimation is about 0.27 mm.

Fig. 11. Displacement estimation result.

VI. CONCLUSION

In this study, we developed a passive bistatic radar system

using geostationary satellite TV signal with commercial-off-

the-shelf hardware. LNB synchronization was used to increase

the coherence for the long-time measurement and thus increase

the SNR and the detection range. High range resolution was

obtained by combing multiple TV channels. The artifacts

caused by frequency gaps among different TV channels were

reduced by means of a super-SVA based method. High azimuth

resolution was achieved by moving the surveillance antenna on

a rail to generate a synthetic aperture. Focused SAR images of

targets were obtained by the back projection algorithm with

reasonable approximations. Displacement of the target in the

scene was estimated by the differential interferometric process.

Compared to current GB-SAR system used for displacement

estimation, the developed system is cheaper as it is does not

need a transmitting unit. Multiple-direction displacement

estimations can be obtained with multiple receivers using

different bistatic geometries. Further work will be devoted to

the generation of a DEM of the study area using an additional

surveillance antenna. Multi-polarization capacity provided by

the BS TV signal is also worthy to be studied. The potential

applications of the developed system includes the continuous

monitoring of landslides, buildings and dams.

ACKNOWLEDGEMENTS

This work was supported by JSPS Grant-in-Aid for Scientific

Research (A) 26249058. The passive radar investigation is

partly supported by the French Centre National de la Recherche

Scientifique (CNRS) PEPS grant.

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